Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021:112:173-204.
doi: 10.1007/978-3-030-76912-3_5.

Automation of Immunoglobulin Glycosylation Analysis

Affiliations
Review

Automation of Immunoglobulin Glycosylation Analysis

Jenifer L Hendel et al. Exp Suppl. 2021.

Abstract

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Keywords: Antibody; Automation; Glycan analysis; Glycomics; High-throughput strategies; Robotization; Sample preparation.

PubMed Disclaimer

References

    1. Adamczyk B, Tharmalingam T, Rudd PM (2012) Glycans as cancer biomarkers. Biochim Biophys Acta 1820:1347–1353 - PubMed - DOI
    1. Adamczyk B, Tharmalingam-Jaikaran T, Schomberg M, Szekrényes Á, Kelly RM, Karlsson NG, Guttman A, Rudd PM (2014) Comparison of separation techniques for the elucidation of IgG N-glycans pooled from healthy mammalian species. Carbohydr Res 389:174–185 - PubMed - DOI
    1. Aich U, Liu A, Lakbub J, Mozdzanowski J, Byrne M, Shah N, Galosy S, Patel P, Bam N (2016) An integrated solution-based rapid sample preparation procedure for the analysis of N-glycans from therapeutic monoclonal antibodies. J Pharm Sci 105:1221–1232 - PubMed - DOI
    1. Alexovič M, Dotsikas Y, Bober P, Sabo J (2018) Achievements in robotic automation of solvent extraction and related approaches for bioanalysis of pharmaceuticals. J Chromatogr B Anal Technol Biomed Life Sci 1092:402–421 - DOI
    1. Alexovič M, Urban PL, Tabani H, Sabo J (2020) Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications. Clin Chim Acta 507:104–116 - PubMed - DOI